Angjoo Kanazawa
Papers
6
Total Citations
882
H-Index
5
About
Angjoo Kanazawa is a leading researcher at the intersection of computer vision and graphics, best known for her transformative work on Neural Radiance Fields (NeRF) and 3D scene understanding. She spearheaded the development of **Nerfstudio** (2023, 528 citations), a modular PyTorch framework that has become the de facto standard for NeRF research, dramatically accelerating experimentation and deployment across vision, graphics, and robotics. Her pioneering work on **Language Embedded Radiance Fields (LERF)** (2023, 291 citations) bridges 3D geometry and natural language, enabling users to query specific 3D locations using open-vocabulary descriptions—a breakthrough for human-robot interaction and scene understanding. Kanazawa has also made foundational contributions to rotation estimation, with her SVD-based analysis (2020) providing rigorous mathematical tools for deep learning on SO(3), and to human mesh recovery, where she developed domain-adaptive pose augmentation techniques (2022) that improve in-the-wild 3D human perception. Her work consistently pushes the boundaries of how machines perceive and interact with the 3D world, earning her widespread recognition as a rising star in computer vision.
Research Focus
Key Achievements
Top Papers
- 1Nerfstudio: A Modular Framework for Neural Radiance Field Development528 citations · 2023
- 2LERF: Language Embedded Radiance Fields291 citations · 2023
- 3An Analysis of SVD for Deep Rotation Estimation32 citations · 2020
- 4Nerfstudio: A Modular Framework for Neural Radiance Field Development19 citations · 2023
- 5Domain Adaptive 3D Pose Augmentation for In-the-Wild Human Mesh Recovery7 citations · 2022
- 6LERF: Language Embedded Radiance Fields5 citations · 2023